235 research outputs found
Imaging Sources with Fast and Slow Emission Components
We investigate two-proton correlation functions for reactions in which fast
dynamical and slow evaporative proton emission are both present. In such cases,
the width of the correlation peak provides the most reliable information about
the source size of the fast dynamical component. The maximum of the correlation
function is sensitive to the relative yields from the slow and fast emission
components. Numerically inverting the correlation function allows one to
accurately disentangle fast dynamical from slow evaporative emission and
extract details of the shape of the two-proton source.Comment: 13 pages, 4 figure
Phocine Distemper Outbreak, the Netherlands, 2002
During the 2002 phocine distemper epidemic, 2,284 seals, primarily harbor seals (Phoca vitulina), were found stranded along the Dutch coast. Stranding pattern varied with age, sex, state of decomposition, wind, and location. Cumulative proportion of deaths (54%) was comparable to that in the first reported epidemic in 1988
A Review of the fossil record of turtles of the clade Baenidae
The fossil record of the turtle clade Baenidae ranges from the Early Cretaceous (Aptian—Albian) to the Eocene. The group is present throughout North America during the Early Cretaceous, but is restricted to the western portions of the continents in the Late Cretaceous and Paleogene. No credible remains of the clade have been reported outside of North America to date. Baenids were warmadapted freshwater aquatic turtles that supported high levels of diversity at times through niche partitioning, particularly by adapting to a broad range of dietary preferences ranging from omnivorous to molluscivorous. Current phylogenies place Baenidae near the split of crown-group Testudines. Within Baenidae three more inclusive, named clades are recognized: Baenodda, Palatobaeninae and Eubaeninae. A taxonomic review of the group concludes that of 49 named taxa, 30 are nomina valida, 12 are nomina invalida and 7 are nomina dubia
LSST: from Science Drivers to Reference Design and Anticipated Data Products
(Abridged) We describe here the most ambitious survey currently planned in
the optical, the Large Synoptic Survey Telescope (LSST). A vast array of
science will be enabled by a single wide-deep-fast sky survey, and LSST will
have unique survey capability in the faint time domain. The LSST design is
driven by four main science themes: probing dark energy and dark matter, taking
an inventory of the Solar System, exploring the transient optical sky, and
mapping the Milky Way. LSST will be a wide-field ground-based system sited at
Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m
effective) primary mirror, a 9.6 deg field of view, and a 3.2 Gigapixel
camera. The standard observing sequence will consist of pairs of 15-second
exposures in a given field, with two such visits in each pointing in a given
night. With these repeats, the LSST system is capable of imaging about 10,000
square degrees of sky in a single filter in three nights. The typical 5
point-source depth in a single visit in will be (AB). The
project is in the construction phase and will begin regular survey operations
by 2022. The survey area will be contained within 30,000 deg with
, and will be imaged multiple times in six bands, ,
covering the wavelength range 320--1050 nm. About 90\% of the observing time
will be devoted to a deep-wide-fast survey mode which will uniformly observe a
18,000 deg region about 800 times (summed over all six bands) during the
anticipated 10 years of operations, and yield a coadded map to . The
remaining 10\% of the observing time will be allocated to projects such as a
Very Deep and Fast time domain survey. The goal is to make LSST data products,
including a relational database of about 32 trillion observations of 40 billion
objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures
available from https://www.lsst.org/overvie
Superluminous supernovae from the Dark Energy Survey
We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I) and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220 < z < 1.998, represent the largest homogeneously selected sample of SLSN events at high redshift. We present the observed g, r, i, z light curves for these SNe, which we interpolate using Gaussian processes. The resulting light curves are analysed to determine the luminosity function of SLSNe-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light-curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of<−16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz
An investigation into heterogeneity of variance for milk and fat yields of Holstein cows in Brazilian herd environments
First cosmology results using SNe Ia from the dark energy survey: analysis, systematic uncertainties, and validation
International audienceWe present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified type Ia supernovae (SNe Ia) from the first three years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift range of 0.01
First cosmology results using type Ia supernovae from the Dark Energy Survey: constraints on cosmological parameters
We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from the first three years of DES-SN, combined with a low-redshift sample of 122 SNe from the literature. Our "DES-SN3YR" result from these 329 SNe Ia is based on a series of companion analyses and improvements covering SN Ia discovery, spectroscopic selection, photometry, calibration, distance bias corrections, and evaluation of systematic uncertainties. For a flat LCDM model we find a matter density Omega_m = 0.331 +_ 0.038. For a flat wCDM model, and combining our SN Ia constraints with those from the cosmic microwave background (CMB), we find a dark energy equation of state w = -0.978 +_ 0.059, and Omega_m = 0.321 +_ 0.018. For a flat w0waCDM model, and combining probes from SN Ia, CMB and baryon acoustic oscillations, we find w0 = -0.885 +_ 0.114 and wa = -0.387 +_ 0.430. These results are in agreement with a cosmological constant and with previous constraints using SNe Ia (Pantheon, JLA)
Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers (Jan , 10.1007/s00330-020-07598-8, 2021)
A Correction to this paper has been published:Radiolog
Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically driven quantitative biomarkers
Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials.Radiolog
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